What is Lagrange all about? Let's talk about something practical.
To be honest, there are plenty of cross-chain projects out there, but very few can guarantee security through mathematics. The Lagrange project is quite interesting; it doesn't mess around with illusions and directly uses zk proofs to clarify multi-chain states for you. For example, if you want to synchronize game achievements from Arbitrum to Sui, traditional solutions either take a long time or rely on the bridge not failing. But with Lagrange's zk co-processor, you can calculate off-chain and directly throw a proof onto the mainnet, which is both fast and stable.
The $LA token is not just a speculation tool; it is required for node staking, governance voting, and paying proof fees. Recently, I saw several DeFi projects testing this on the testnet, saving about 80-90% on gas fees. If it really works, in the future, chain games and RWA projects will probably rush to integrate #Lagrange @Lagrange Official $LA .
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$SOL LYS Labs, a technology company, has just secured 4 million dollars to make the Solana blockchain smarter with artificial intelligence (AI). What does this mean? - Easy-to-understand data: They will use AI to take the complex data from Solana and turn it into simple and useful information. - AI agents: They want to create "AI agents" that can perform operations and tasks directly on the Solana network. - Developer assistant: They already have an AI assistant named Solexys, which helps over 200 people work with the blockchain. In summary, LYS Labs aims to bring AI to Solana to make the network more powerful and easier to use, both for developers and users.
🤯 On August 18, Lagrange announced the results of the launch of DeepProve-1, the first zkMl system that demonstrates complete LLM inference. DeepProve-1 is the first zkML (zero-knowledge machine learning) system developed by Lagrange Labs that allows generating cryptographic proofs of complete inferences from large language models (LLMs) like GPT-2. DeepProve-1. Features and achievements: First complete LLM inference proof, DeepProve-1 managed to generate a zero-knowledge proof for the complete inference of GPT-2, a large language model from OpenAI. Verifiability in AI, introduces verifiability as a core feature in modern AI systems, extending this to full transformer architectures. Support for complex structures, handles computation graphs with residual connections, parallel branches, and variable length inputs, typical in LLMs. Applications and relevance: security and privacy: Allows verifying the results of an LLM without revealing input data or model details, crucial for applications in defense, healthcare, finance, and infrastructure. Auditability, facilitates the auditing of decisions made by LLMs without compromising data privacy or the intellectual property of the model. Developments and future plans Performance optimization: Lagrange Labs is working on improving cryptographic efficiency and parallelism to make DeepProve-1 more practical in production environments. Extension to other LLMs, the next goal is to support models like Meta's LLAMA, one of the most adopted open-source LLMs. DeepProve-1 is a significant advancement in verifiable AI, enabling cryptographic proofs of LLM inferences. $LA @Lagrange Official #lagrange #creadorpad #lagrangeholder
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